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Urban areas are being recognized as ecosystems, where biodiversity is essential for sustaining their functionality. Healthy ecosystems offer numerous services that contribute to the well-being of human populations. The EU Biodiversity Strategy and the Nature Restoration law call for no-net loss of urban green spaces and a minimum 10% tree canopy cover in European cities. This commitment is driving a surge in city tree planting projects, with expectations for further increase in the coming years. In this context, we present an investigation focused on the multiscale mapping and monitoring of urban green biodiversity, with a primary emphasis on trees. Urban trees, besides providing various ecosystem services, play a crucial role in mitigating the urban heat load during summers, thereby alleviating adverse effects on human health, and reducing energy consumption. Unfortunately, the challenging conditions within urban environments, including increased temperatures and water scarcity due to impervious surfaces, can impact the phenology and physiology of trees, often compromising their health and functionality. In order to better explore these aspects, we introduce an application based on Google Earth Engine with the aim to extract geospatial data related to tree cover and temperatures across various spatial scales in urban environments. Utilizing machine learning algorithms, the application downscales thermal infrared satellite imagery and classifies vegetation features. Users have the flexibility to investigate the relationship between temperatures and vegetation by selecting specific time windows and areas of interest, along with access to significant spectral indices and correlation coefficients. In a pilot case study on the city of Milan, we use the application to perform a detailed analysis at the tree species level, involving the assessment of individual tree canopy temperature response in different areas of the city. This application aims to provide researchers, urban planners, green managers, and other professionals with a valuable tool to comprehend the spatial dynamics of vegetation in urban environments, assess the impacts of stressors on their fitness, and in the long run to evaluate the effectiveness of mitigation efforts, such as urban reforestations and tree planting.
Bottaro et al. (Fri,) studied this question.